Scaling of potential evapotranspiration with MODIS data reproduces flux observations and catchment water balance observations across Australia

摘要

We developed a new algorithm for estimating monthly actual evapotranspiration(AET)based on surface reflectance from MODIS-Terra and interpolated climate data.The algorithm uses monthly values of the Enhanced Vegetation Index(EVI)and the Global Vegetation Moisture Index(GVMI)derived from the MODIS nadir bidirectional reflectance distribution function-adjusted reflectance product(MOD43B4)to scale Priestley-Taylor potential evapotranspiration derived from the climate Surfaces.The EVI is associated with evapotranspiration through its relationship with leaf area index.The GVMI allows separation between surface water and bare soil when EVI is low and provides information on vegetation water content when EVI is high.The model was calibrated using observed AET data from seven sites in Australia, including two forests,two open savannas,a grassland,a floodplain and a lake.Model outputs were compared with four year average difference between precipitation and streamflow(a surrogate for mean AET)in 227 unimpaired catchments across Australia. We tested four different model configurations and found that the best results both in the calibration and evaluation datasets were obtained when a precipitation interception term (E-j)and the GVMI were incorporated into the model.The E-j term and the GVMI improved AET estimates in the forest,savanna and grassland sites and in the lake and floodplain sites respectively.The most comprehensive model estimated monthly AET at the seven calibration sites with a RMSE of 18.0 mm mo(-1)(22% of the mean AET,r(2)=0.84).In the evaluation dataset,mean annual AET was estimated with a RMSE of 137.44 mm y(-1)(19% of the mean AET,r(2)=0.61).The model was able to reproduce the main spatial and temporal patterns in AET across Australia. The main advantages of the proposed model are that it uses a single set of parameters(i.e.does not need an auxiliary land cover map) and that it is able to estimate AFT in areas with significant direct evaporation,including lakes and floodplains. Crown Copyright(C)2009 Published by Elsevier B.V.All rights reserved.